rAmChart package

The package rAmChart allows you to draw JavaScript charts wich are by nature interactive. Its architecture is based on S4 classes and corresponds almost exactly to the original library AmCharts.

For readability matters, we do not detail much htmlwidgets features on the present website. For more details consult directly http://www.htmlwidgets.org.

Getting started

pipeR

When loading the packge, you note that it is fully compatible with other plot methods since it uses S4 signature for each functionnality.

## 
## Attaching package: 'rAmCharts'
## 
## The following object is masked from 'package:graphics':
## 
##     title

In the rest of this short introduction, you will always see the symbol %>>% introduced by the package pipeR. For more details, please refer to the official tutorial.

For the present quick introduction on rAmCharts, we just have to keep in mind that using this syntax, the left hand code is evaluated and passed as the first argument of the function which follow %>>% (or alternatively it can can be any argument by indicating a . using () or {} ).

For example:

data(iris)
summary(iris, digits = 2)

##   Sepal.Length  Sepal.Width   Petal.Length  Petal.Width        Species  
##  Min.   :4.3   Min.   :2.0   Min.   :1.0   Min.   :0.1   setosa    :50  
##  1st Qu.:5.1   1st Qu.:2.8   1st Qu.:1.6   1st Qu.:0.3   versicolor:50  
##  Median :5.8   Median :3.0   Median :4.3   Median :1.3   virginica :50  
##  Mean   :5.8   Mean   :3.1   Mean   :3.8   Mean   :1.2                  
##  3rd Qu.:6.4   3rd Qu.:3.3   3rd Qu.:5.1   3rd Qu.:1.8                  
##  Max.   :7.9   Max.   :4.4   Max.   :6.9   Max.   :2.5

is equivalent to:

library(pipeR)
data(iris)
iris %>>% summary( digits = 2 )

##   Sepal.Length  Sepal.Width   Petal.Length  Petal.Width        Species  
##  Min.   :4.3   Min.   :2.0   Min.   :1.0   Min.   :0.1   setosa    :50  
##  1st Qu.:5.1   1st Qu.:2.8   1st Qu.:1.6   1st Qu.:0.3   versicolor:50  
##  Median :5.8   Median :3.0   Median :4.3   Median :1.3   virginica :50  
##  Mean   :5.8   Mean   :3.1   Mean   :3.8   Mean   :1.2                  
##  3rd Qu.:6.4   3rd Qu.:3.3   3rd Qu.:5.1   3rd Qu.:1.8                  
##  Max.   :7.9   Max.   :4.4   Max.   :6.9   Max.   :2.5

or even

library(pipeR)
data(iris)
iris %>>% ( summary(object = ., digits = 2) )

##   Sepal.Length  Sepal.Width   Petal.Length  Petal.Width        Species  
##  Min.   :4.3   Min.   :2.0   Min.   :1.0   Min.   :0.1   setosa    :50  
##  1st Qu.:5.1   1st Qu.:2.8   1st Qu.:1.6   1st Qu.:0.3   versicolor:50  
##  Median :5.8   Median :3.0   Median :4.3   Median :1.3   virginica :50  
##  Mean   :5.8   Mean   :3.1   Mean   :3.8   Mean   :1.2                  
##  3rd Qu.:6.4   3rd Qu.:3.3   3rd Qu.:5.1   3rd Qu.:1.8                  
##  Max.   :7.9   Max.   :4.4   Max.   :6.9   Max.   :2.5

---

Quick tour:

Example

Start with a simple pie chart

library(rAmCharts)
amPieChart(theme ="light", titleField = "key", valueField = "value"
) %>>% setDataProvider(data.frame(key = c("FR", "US"), value = c(20,10))
) %>>% setLegend( position = "right"
) %>>% plot

Details…

If you look at the corresponding pie chart example from the original JavaScript library on http://www.amcharts.com/demos/, you notice that the javascript source code looks like:

{
"type": "pie",
"theme": "light",
"dataProvider": [ {
"country": "FR",
"litres": 20
}, {
"country": "US",
"litres": 10
}],
"valueField": "litres",
"titleField": "country",
}

Although the syntax appears very different, it has similarities. If you observe the result before calling the plot method, you see a global list containing each parameter mentionned in the code:

library(rAmCharts)
amPieChart(theme ="light", titleField = "key", valueField = "value"
) %>>% setDataProvider(data.frame(key = c("FR", "US"), value = c(20,10))
)

## $pathToImages
## [1] "http://www.amcharts.com/lib/3/images/"
## 
## $titleField
## [1] "key"
## 
## $valueField
## [1] "value"
## 
## $dataProvider
## $dataProvider[[1]]
## $dataProvider[[1]]$key
## [1] FR
## Levels: FR US
## 
## $dataProvider[[1]]$value
## [1] 20
## 
## 
## $dataProvider[[2]]
## $dataProvider[[2]]$key
## [1] US
## Levels: FR US
## 
## $dataProvider[[2]]$value
## [1] 10
## 
## 
## 
## $theme
## [1] "light"
## 
## $type
## [1] "pie"

This list can be easily mapped to the previous JavaScript code with the following tips:

• A JavaScript object corresponds to a R list
• A JavaScript array (a wrapper for an object) also corresponds to a R list

This structure and mapping are fundamental to the how we construct charts with the package.

The key is to imagine the function call as a list containing every properties for an S4 class initializer:

library(rAmCharts)
class(
  amPieChart(theme ="light", titleField = "key", valueField = "value")
)

## [1] "AmChart"
## attr(,"package")
## [1] "rAmCharts"

• Each element from the function call is a first level property.
• Other complex first level properties have their own dedicated functions for which the first argument is always the inherited S4 class object.

To illustrate, setDataProvider is a valid method for setting chart data of classes AmChart and DatSet:

showMethods("setDataProvider")

## Function: setDataProvider (package rAmCharts)
## .Object="AmChart", dataProvider="data.frame"
## .Object="DataSet", dataProvider="data.frame"

Therefore, it can be used in those contexts:

amChart([first level properties]) %>>% setDataProvider(dataProvider = ...)

dataSet([first level properties]) %>>% setDataProvider(dataProvider = ...)

Customization…

Currently you can draw any object derived from:

• AmCharts API: http://docs.amcharts.com/3/javascriptcharts
• AmStockCharts API: http://docs.amcharts.com/3/javascriptstockchart

This means you can customize you chart in various ways !

For instance, we can move the default linked label JS chart by amCharts (which must be kept if using the library without license). We also can switch the theme:

library(rAmCharts)
amPieChart(theme ="chalk", titleField = "key", valueField = "value",
           creditsPosition = "bottom-left"
) %>>% setDataProvider(data.frame(key = c("FR", "US"), value = c(20,10))
) %>>% setLegend( position = "right"
) %>>% plot

Few demos

Basics

amXYChart

library(rAmCharts)
amXYChart(theme = "default", startDuration = 0.5, marginLeft = 46, marginBottom = 35
) %>>% setDataProvider(data.frame( y = c(10,5,-10,-6,15,13,1),  x = c(14,3,8,5,-4,1,6),
                                   value = c(59,50,19,65,92,8,16), y2 = c(-5,-15,-4,-5,-10,-2,0),
                                   x2 = c(-3,-8,6,-6,-8,0,-3), value2 = c(44,12,35,168,102,41,16))
) %>>% addValueAxes(position = "bottom", axisAlpha = 0
) %>>% addValueAxes(minMaxMultiplier = 1.2, position = "left", axisAlpha = 0
) %>>% addGraph(balloonText = "x:<b>[[x]]</b> y:<b>[[y]]</b><br>value:<b>[[value]]</b>",
                bullet = "circle", bulletBorderAlpha = 0.2, bulletAlpha = 0.8, lineAlpha=0,
                fillAlphas = 0, valueField = "value", xField = "x",yField = "y", maxBulletSize = 100
) %>>% addGraph(balloonText = "x:<b>[[x]]</b>y:<b>[[y]]</b><br>value:<b>[[value]]</b>",
                bullet="diamond",bulletBorderAlpha=0.2, bulletAlpha = 0.8, lineAlpha = 0,
                fillAlphas = 0,valueField = "value2", xField = "x2", yField = "y2",
                maxBulletSize = 100
) %>>% setExport %>>% plot

gaugeChart

library(rAmCharts)
amAngularGaugeChart(theme = "light"
) %>>% addArrow(value = 100
) %>>% addAxe(gaugeAxis (bottomText = "100 km/h", endValue = 220, valueInterval = 10
) %>>% addBand(color = "#00CC00", endValue = 90, startValue = 0
) %>>% addBand(color = "#ffac29", endValue = 130, startValue = 90
) %>>% addBand(color = "#ea3838", endValue = 220, startValue = 130, innerRadius = "95%")
) %>>% setExport %>>% plot

funnelChart

library(rAmCharts)
library(pipeR)
amFunnelChart(theme = "light", neckHeight = "30%", neckWidth = "40%", titleField = "title",
              valueField = "value", creditsPosition = "bottom-left", 
              dataProvider = data.frame(title = c("Website visits", "Downloads"),
                                        value = c(300, 123))
) %>>% plot

Elaborated

Column and line mix

See http://www.amcharts.com/demos/column-and-line-mix/

library(rAmCharts)
library(pipeR)
amSerialChart(addClassNames = TRUE, theme = "light", autoMargins = FALSE, marginLeft = 30,
              marginRight = 8, marginTop = 10, marginBottom = 26, startDuration = 1,
              categoryField = "year"
) %>>% setDataProvider(data.frame(year  =  c(2010, 2011, 2012, 2013, 2014),
                                  income  =  c(20.4, 20.6, 24.3, 21.5, 22.3), 
                                  expenses  =  c(31.5, 32.4, 25.6, 22.6, 24.9),
                                  dashLengthColumn = c(NA, NA, NA, NA, 5), 
                                  alpha = c(NA, NA, NA, NA, 0.2), 
                                  additional = c("", "", "", "", "(projection)"))
) %>>% setBalloon(adjustBorderColor = FALSE, horizontalPadding = 10,
                  verticalPadding = 8,color = "#ffffff"
) %>>% addValueAxes(axisAlpha = 0, position = "left"
) %>>% addGraph(alphaField = "alpha", fillAlphas = 1, title = "Income",
                type = "column", valueField = "income",
                balloonText = "<span style = 'font-size:12px;'>[[title]] in [[category]]:<br><span style = 'font-size:20px;'>[[value]]</span> [[additional]]</span>", 
                 dashLengthField = "dashLengthColumn"
) %>>% addGraph(id = "graph2", bullet = "round", lineThickness = 3, bulletSize = 7,
                balloonText = "<span style = 'font-size:12px;'>[[title]] in [[category]]:<br><span style = 'font-size:20px;'>[[value]]</span> [[additional]]</span>", 
                bulletBorderAlpha = 1, bulletColor = "#FFFFFF",
                useLineColorForBulletBorder = TRUE, bulletBorderThickness = 3, 
                fillAlphas = 0, lineAlpha = 1, title = "Expenses", valueField = "expenses"
) %>>% setCategoryAxis(gridPosition = "start", axisAlpha = 0, tickLength = 0
) %>>% setExport %>>% plot

Column with rotated series

See http://www.amcharts.com/demos/exporting-chart-to-image/

library(rAmCharts)
library(pipeR)

amSerialChart(theme = "dark", startDuration = 2, categoryField = "country", depth3D = 40,
               angle = 30
) %>>% setDataProvider(data.frame(
  country = c("USA", "China", "Japan", "Germany", "UK", "France", "India", "Spain", "Netherlands", "Russia"), 
  visits = c(3025, 1882, 1809, 1322, 1122, 1114, 984, 711, 665, 580), 
  color = c("#FF0F00", "#FF6600", "#FF9E01", "#FCD202", "#F8FF01", "#B0DE09", "#04D215", "#0D8ECF", "#0D52D1", "#2A0CD0"))
) %>>% addGraph(balloonText = "<b>[[category]]: [[value]]</b>", fillColorsField = "color", 
                 fillAlphas = 0.85, lineAlpha = 0.1, type = "column", valueField = "visits"
) %>>% setChartCursor(categoryBalloonEnabled = FALSE, cursorAlpha = 0, zoomable = FALSE
) %>>% setCategoryAxis(gridPosition = "start", labelRotation = 45, axisAlpha = 0, gridAlpha = 0
) %>>% setExport %>>% plot

Stacked areas

See http://www.amcharts.com/demos/stacked-area/

library(rAmCharts)
library(pipeR)

amSerialChart(theme = "light", marginRight = 30, plotAreaBorderAlpha = 0,
               categoryField = "year"
) %>>% setDataProvider(data.frame(
  year  =  1994:2012, 
  cars  =  c(15, 13, 14, 15, 16, 18, 19, 22, 24, 20, 24, 25, 26, 35, 36, 37, 38, 39, 40), 
  motorcycles  =  c(15, 13, 14, 15, 16, 18, 19, 22, 24, 20, 24, 25, 26, 35, 36, 37, 38, 39, 40), 
  bicycles  =  c(15, 13, 14, 15, 16, 18, 19, 22, 24, 20, 24, 25, 26, 35, 36, 37, 38, 39, 40))
) %>>% setLegend(equalWidths = FALSE, periodValueText = "total: [[value.sum]]", position = "top", valueAlign = "left", valueWidth = 100
) %>>% addValueAxes(stackType = "regular", gridAlpha = 0.07, position = "left",
                    title = "Traffic incidents"
) %>>% addGraph(balloonText = "<img src = 'http://www.amcharts.com/lib/3/images/car.png' style = 'vertical-align:bottom; margin-right: 10px; width:28px; height:21px;'><span style = 'font-size:14px; color:#000000;'><b>[[value]]</b></span>", 
                 fillAlphas = 0.6, hidden = TRUE, lineAlpha = 0.4, title = "Cars",
                valueField = "cars"
) %>>% addGraph(balloonText = "<img src = 'http://www.amcharts.com/lib/3/images/motorcycle.png' style = 'vertical-align:bottom; margin-right: 10px; width:28px; height:21px;'><span style = 'font-size:14px; color:#000000;'><b>[[value]]</b></span>", 
                 fillAlphas = 0.6, lineAlpha = 0.4, title = "Motorcycles", valueField = "motorcycles"
) %>>% addGraph(balloonText = "<img src = 'http://www.amcharts.com/lib/3/images/bicycle.png' style = 'vertical-align:bottom; margin-right: 10px; width:28px; height:21px;'><span style = 'font-size:14px; color:#000000;'><b>[[value]]</b></span>", 
                 fillAlphas = 0.6, lineAlpha = 0.4, title = "Bicycles", valueField = "bicycles"
) %>>% setChartCursor(cursorAlpha = 0
) %>>% setChartScrollbar(
) %>>% setCategoryAxis(startOnAxis = TRUE, axisColor = "#DADADA", gridAlpha = 0.07
) %>>% setGuides(list(guide(category = "2001", toCategory = "2003", lineColor = "#CC0000",
                            lineAlpha = 1, fillAlpha = 0.2, fillColor = "#CC0000", dashLength = 2,
                            inside = TRUE, labelRotation = 90,
                            label = "fines for speeding increased"),
                      guide(category = "2007", lineColor = "#CC0000", lineAlpha = 1,
                            dashLength = 2, inside = TRUE, labelRotation = 90,
                            label =  "motorcycle fee introduced"))
) %>>% setExport %>>% plot

Waterfall chart

See http://www.amcharts.com/demos/waterfall-chart/

library(rAmCharts)
library(pipeR)

amSerialChart(theme = "light", startDuration = 1, columnWidth = 0.6, categoryField = "name", pathToImages = "http://www.amcharts.com/lib/3/images/"
) %>>% setDataProvider( data.frame(
  name = c("Income A", "Income B", "Total Income", "Expenses A", "Expenses B", "Revenue"), 
  open  =  c(0, 11.13, 0, 12.92, 8.64, 0), 
  close =  c(11.13, 15.81, 15.81, 15.81, 12.92, 8.64), 
  color  =  c("#54cb6a", "#54cb6a", "#169b2f", "#cc4b48", "#cc4b48", "#1c8ceb"), 
  balloonValue  =  c(11.13, 4.68, 15.81, 2.89, 4.24, 11.13) )
) %>>% addValueAxes(axisAlpha = 0, gridAlpha = 0.1, position = "left"
) %>>% addGraph(balloonText = "<span style = 'color:[[color]]'>[[category]]</span><br><b>$[[balloonValue]] Mln</b>", 
                 colorField = "color", fillAlphas = 0.8, labelText = "$[[balloonValue]]",
                lineColor = "#BBBBBB", openField = "open", type = "column", valueField = "close"
) %>>% addTrendLine(dashLength = 3, finalCategory = "Income B",
                    finalValue = 11.13, initialCategory = "Income A",
                    initialValue = 11.13, lineColor = "#888888"
) %>>% addTrendLine(dashLength = 3, finalCategory = "Expenses A", finalValue = 15.81, initialCategory = "Income B", initialValue = 15.81, lineColor = "#888888"
) %>>% addTrendLine(dashLength = 3, finalCategory = "Expenses A",
                    finalValue = 15.81, initialCategory = "Income B",
                    initialValue = 15.81, lineColor = "#888888"
) %>>% addTrendLine(dashLength = 3, finalCategory = "Expenses B",
                    finalValue = 12.92, initialCategory = "Expenses A",
                    initialValue = 12.92, lineColor = "#888888"
) %>>% addTrendLine(dashLength = 3, finalCategory = "Revenue", finalValue = 8.64,
                    initialCategory = "Expenses B", initialValue = 8.64, lineColor = "#888888"
) %>>% setCategoryAxis(gridPosition = "start", axisAlpha = 0, gridAlpha = 0.1
) %>>% setExport %>>% plot

---

Candle stick chart

See http://www.amcharts.com/demos/candlestick-chart/

library(rAmCharts)
library(pipeR)
library(data.table)

# ---------------------------
# Create the dataProvider ---
# ---------------------------
start <- as.POSIXct("01-01-2015", format = "%d-%m-%Y")
end <- as.POSIXct("31-12-2015", format = "%d-%m-%Y")
date <- seq.POSIXt(from = start, to = end, by = "day")
date <- format(date, "%m-%d-%Y")
n <- 100
low <- c() ; open <- c() ; close <- c() ; high <- c()

invisible(
  sapply(1:length(date), function(i)
  {
    sample <- rnorm(n, mean = sample(1:10, 1), sd = sample(1:10/10, 1))
    quant <- boxplot(sample, plot = FALSE)$stats
    low <<- c(low, quant[1])
    open <<- c(open, quant[2])
    close <<- c(close, quant[4])
    high <<- c(high, quant[5])
  })
)
dp <- data.table(date = date, low = round(low, 2), open = round(open, 2),
                 close = round(close, 2), high = round(high, 2))

# --------------
# Draw chart ---
# --------------
amSerialChart(categoryField = "date", theme = "light",
              dataDateFormat = "YYYY-MM-DD", dataProvider = dp
) %>>% setCategoryAxis(parseDates = TRUE
) %>>% addValueAxes(position = "left"
) %>>% addGraph(id = "g1",
                 balloonText = "Open : <b>[[open]]</b><br>Low =<b>[[low]]</b><br>High =<b>[[high]]</b><br>Close =<b>[[close]]</b><br>",
                 closeField = "close", fillColors = "#7f8da9", highField = "high",
                 lineColor = "#7f8da9", lineAlpha = 1, lowField = "low",
                 fillAlphas = "0.9",  negativeFillColors = "#db4c3c", negativeLineColor = "#db4c3c",
                 openField = "open", title = "Price:", type = "candlestick", valueField = "close"
) %>>% setChartCursor(valueLineEnabled = TRUE, valueLineBalloonEnabled = TRUE
) %>>% setChartScrollbar(graph = "g1"
) %>>% addListener("rendered", "function(event) { event.chart.zoomToIndexes(event.chart.dataProvider.length - 10, event.chart.dataProvider.length - 1) }"
) %>>% setExport(position = "top-left") %>>% plot

---

AmSerialChart: example of boxPlot

library(rAmCharts)
library(pipeR)
library(data.table)

# ---------------------------
# Create the dataProvider ---
# ---------------------------
start <- as.POSIXct("01-01-2015", format = "%d-%m-%Y")
end <- as.POSIXct("31-12-2015", format = "%d-%m-%Y")
date <- seq.POSIXt(from = start, to = end, by = "day")
date <- format(date, "%m-%d-%Y")
n <- 100
low_outlier <- c() ; low <- c() ; open <- c()
close <- c() ; high <- c() ; high_outlier <- c() 
median <- c()
invisible(
  sapply(1:length(date), function(i)
  {
    sample <- rnorm(n, mean = sample(1:10, 1), sd = sample(1:10/10, 1))
    quant <- boxplot(sample, plot = FALSE)$stats
    low_outlier <<- c(low_outlier, quant[1])
    low <<- c(low, quant[1])
    open <<- c(open, quant[2])
    median <<- c(median, quant[3])
    close <<- c(close, quant[4])
    high <<- c(high, quant[5])
    high_outlier <<- c(high_outlier, quant[5])
  })
)
dp <- data.table(date = date, low_outlier = round(low_outlier, 2), low = round(low, 2),
                 open = round(open, 2), median = round(median, 2), close = round(close, 2),
                 high = round(high, 2), high_outlier = round(high_outlier, 2) )

# --------------
# Draw chart ---
# --------------
amSerialChart(categoryField = "date", theme = "light",
              dataDateFormat = "MM-DD-YYYY", dataProvider = dp
) %>>% setCategoryAxis(parseDates = TRUE
) %>>% addValueAxes(position = "left"
) %>>% addGraph(id = "g1", type = "candlestick",
                balloonText = "Low = <b>[[low_outlier]]</b><br/>1st quart. = <b>[[open]]</b><br/>Median = <b>[[median]]</b><br/>3rd quart. = <b>[[close]]</b><br/>High = <b>[[high_outlier]]</b><br/>",
                closeField = "close", fillColors = "#7f8da9", highField = "high",
                lineColor = "#7f8da9", lineAlpha = 1, lowField = "low",
                fillAlphas = "0.9",  negativeFillColors = "#db4c3c", negativeLineColor = "#db4c3c",
                openField = "open", title = "Price:", valueField = "close"
) %>>% addGraph(id = "g2", type = "step", valueField = "median",
                noStepRisers = TRUE, balloonText = ""
) %>>% addGraph(id = "g3", type = "step", valueField = "low_outlier",
                noStepRisers = TRUE, balloonText = ""
) %>>% addGraph(id = "g4", type = "step", valueField = "high_outlier",
                noStepRisers = TRUE, balloonText = ""
) %>>% setChartCursor(valueLineEnabled = TRUE, valueLineBalloonEnabled = TRUE
) %>>% setChartScrollbar(parseDates = TRUE
) %>>% addListener("rendered", "function(event) { event.chart.zoomToIndexes(event.chart.dataProvider.length - 10, event.chart.dataProvider.length - 1) }"
) %>>% setExport(position = "bottom-right") %>>% plot()

---

Stock chart with multiple data sets

See http://www.amcharts.com/demos/multiple-data-sets/

library(rAmCharts)
library(pipeR)

# ---------------------------
# Create the dataProvider ---
# ---------------------------
firstDate <- Sys.Date()
chartData1 <- as.data.frame(t(sapply(0:20, FUN = function(i)
{
  date <- format(firstDate + i, "%m/%d/%Y")
  a <- round(runif(1) * (40 + i)) + 100 + i
  b <- round(runif(1) * (1000 + i)) + 500 + i * 2
  c(date = date, value = a,  volume = b)
})))

chartData2 <- as.data.frame(t(sapply(0:20, FUN = function(i)
{
  date <- format(firstDate + i, "%m/%d/%Y")
  a <- round(runif(1) * (100 + i)) + 200 + i
  b <- round(runif(1) * (1000 + i)) + 600 + i * 2
  c(date = date, value = a,  volume = b)
})))

chartData3 <- as.data.frame(t(sapply(0:20, FUN = function(i)
{
  date <- format(firstDate + i, "%m/%d/%Y")
  a <- round(runif(1) * (100 + i)) + 200 + i
  b <- round(runif(1) * (1000 + i)) + 600 + i * 2
  c(date = date, value = a,  volume = b)
})))

chartData4 <- as.data.frame(t(sapply(0:20, FUN = function(i)
{
  date <- format(firstDate + i, "%m/%d/%Y")
  a <- round(runif(1) * (100 + i)) + 200 + i
  b <- round(runif(1) * (1000 + i)) + 600 + i * 2
  c(date = date, value = a,  volume = b)
})))

# --------------
# Draw chart ---
# --------------
amStockChart(theme = "light"
) %>>% addDataSet(dataSet(title = "first data set", categoryField = "date",
                            dataProvider = chartData1) %>>%
                     addFieldMapping(fromField = "value", toField = "value") %>>%
                     addFieldMapping(fromField = "volume", toField = "volume")
) %>>% addDataSet(dataSet(title = "second data set", categoryField = "date",
                            dataProvider = chartData2) %>>%
                     addFieldMapping(fromField = "value", toField = "value") %>>%
                     addFieldMapping(fromField = "volume", toField = "volume")
) %>>% addDataSet(dataSet(title = "third data set", categoryField = "date",
                            dataProvider = chartData3) %>>%
                     addFieldMapping(fromField = "value", toField = "value") %>>%
                     addFieldMapping(fromField = "volume", toField = "volume")
) %>>% addDataSet(dataSet(title = "fourth data set", categoryField = "date",
                            dataProvider = chartData4) %>>%
                     addFieldMapping(fromField = "value", toField = "value") %>>%
                     addFieldMapping(fromField = "volume", toField = "volume")
) %>>% addPanel(stockPanel(showCategoryAxis = FALSE, title = "Value", percentHeight = 70) %>>%
                   addStockGraph(id = "g1", valueField = "value", comparable = TRUE,
                                 compareField = "value", balloonText = "[[title]] =<b>[[value]]</b>",
                                 compareGraphBalloonText = "[[title]] =<b>[[value]]</b>"
                  ) %>>% setStockLegend(periodValueTextComparing = "[[percents.value.close]]%",
                                          periodValueTextRegular = "[[value.close]]")
) %>>% addPanel(stockPanel(title = "Volume", percentHeight = 30) %>>%
                   addStockGraph(valueField = "volume", type = "column",
                                 fillAlphas = 1) %>>%
                   setStockLegend(periodValueTextRegular = "[[value.close]]")
) %>>% setChartScrollbarSettings(graph = "g1"
) %>>% setChartCursorSettings(valueBalloonsEnabled = TRUE, fullWidth = TRUE,
                               cursorAlpha = 0.1, valueLineBalloonEnabled = TRUE,
                               valueLineEnabled = TRUE, valueLineAlpha = 0.5
) %>>% setPeriodSelector(periodSelector(position = "left") %>>%
                            addPeriod(period = "MM", selected = TRUE, count = 1, label = "1 month") %>>%
                            addPeriod(period = "MAX", label = "MAX")
) %>>% setDataSetSelector(position = "left"
) %>>% setPanelsSettings(recalculateToPercents = FALSE
) %>>% plot

Stock chart with dates

See http://www.amcharts.com/demos/multiple-data-sets/

library(rAmCharts)
library(pipeR)
library(data.table)

# ---------------------------
# Create the dataProvider ---
# ---------------------------
start <- as.POSIXct("01-01-2015", format = "%d-%m-%Y")
end <- as.POSIXct("31-12-2015", format = "%d-%m-%Y")
period <- seq.POSIXt(from = start, to = end, by = "10 min")
n <- length(period)
periodTemp <- seq.POSIXt(from = start, to = end, by = "3 hour")
nTemp <- length(periodTemp)
### Generate mesures ----
charge <- rnorm(n, mean = 500, sd= 200)
charge[ which(charge < 0) ] <- rnorm(length(which(charge < 0)), mean = 200, sd = 10)
temp <- rnorm(nTemp, mean = 15, sd = 10)
dtCharge <- data.table::data.table(charge, date = period)
setkey(dtCharge, date)
dtTemp <- data.table::data.table(temperature = temp, date = periodTemp)
setkey(dtTemp , date)
dp <- dtTemp[dtCharge]
dp <- dp[, date := format(date, "%m-%d-%Y %H:%M:%S")][1:10000]

# --------------
# Draw chart ---
# --------------
amStockChart(theme = "default" , dataDateFormat = "MM-DD-YYYY JJ:NN:SS"
) %>>% addDataSet(dataSet(title = "Courbe de charge", categoryField = "date") %>>%
                    setDataProvider(dp, keepNA = FALSE) %>>%
                    addFieldMapping(fromField = "charge", toField = "charge") %>>%
                    addFieldMapping(fromField = "temperature", toField = "temperature") %>>%
                    addStockEvent( date = "01-02-2015 23:00:00", type = "sign", graph ="g1",
                                    text = "I am a stockEvent", description = "I am a property of a DataSet")
) %>>% addPanel(stockPanel(showCategoryAxis = FALSE, title = "Charge", percentHeight = 70) %>>%
                   addStockGraph(id = "g1", valueField = "charge", comparable = TRUE,
                                 compareField = "charge", balloonText = "[[title]] =<b>[[value]]</b>",
                                 compareGraphBalloonText = "[[title]] =<b>[[value]]</b>"
                  ) %>>% setStockLegend(periodValueTextComparing = "[[percents.value.close]]%",
                                          periodValueTextRegular = "[[value.close]]")
) %>>% addPanel(stockPanel(title = "Temperature", percentHeight = 30) %>>%
                   addStockGraph(valueField = "temperature", fillAlphas = 1) %>>%
                   setStockLegend(periodValueTextRegular = "[[value.close]]")
) %>>% setChartScrollbarSettings(graph = "g1"
) %>>% setChartCursorSettings(valueBalloonsEnabled = TRUE, fullWidth = TRUE,
                               cursorAlpha = 0.1, valueLineBalloonEnabled = TRUE,
                               valueLineEnabled = TRUE, valueLineAlpha = 0.5
) %>>% setPeriodSelector(periodSelector(position = "left") %>>%
                            addPeriod(period = "MM", selected = TRUE,
                                      count = 1, label = "1 month") %>>%
                            addPeriod(period = "MAX", label = "MAX")
) %>>% setDataSetSelector(position = "left"
) %>>% setCategoryAxesSettings(minPeriod = "ss"
) %>>% setPanelsSettings(recalculateToPercents = FALSE
) %>>% plot